Search for: All records

This study investigates boreal spring events of Pacific Meridional Mode (PMM) from 1950 to 2022, revealing that cold PMM is more effective in triggering subsequent La Niña compared to warm PMM's induction of following El Niño. This asymmetry stems from the varying origins and sub‐efficacies of PMM groups. The cold PMM is primarily initiated by pre‐existing La Niña, while the warm PMM is comparably activated by pre‐existing El Niño and internal atmospheric dynamics. PMMs initiated by pre‐existing El Niño or La Niña play a crucial role in determining the efficacies of PMMs in triggering subsequent El Niño‐Southern Oscillation (ENSO). The strong discharge of pre‐existing El Niño hampers warm PMM's induction of subsequent El Niño, whereas weak recharge from pre‐existing La Niña enhances the efficacy of cold PMM in inducing subsequent La Niña. Comprehending not only the PMM phase but also its origin is crucial for ENSO research and prediction.

Utilizing a 2200-yr CESM1 preindustrial simulation, this study examines the influence of property distinctions between single-year (SY) and multiyear (MY) La Niñas on their respective impacts on winter surface air temperatures across mid–high-latitude continents in the model, focusing on specific teleconnection mechanisms. Distinct impacts were identified in four continent sectors: North America, Europe, Western Siberia (W-Siberia), and Eastern Siberia (E-Siberia). The typical impacts of simulated SY La Niña events are featured with anomalous warming over Europe and W&E-Siberia and anomalous cooling over North America. Simulated MY La Niña events reduce the typical anomalous cooling over North America and the typical anomalous warming over W&E-Siberia but intensify the typical anomalous warming over Europe. The distinct impacts of simulated MY La Niñas are more prominent during their first winter than during the second winter, except over W-Siberia, where the distinct impact is more pronounced during the second winter. These overall distinct impacts in the CESM1 simulation can be attributed to the varying sensitivities of these continent sectors to the differences between MY and SY La Niñas in their intensity, location, and induced sea surface temperature anomalies in the Atlantic Ocean. These property differences were linked to the distinct climate impacts through the Pacific North America, North Atlantic Oscillation, Indian Ocean–induced wave train, and tropical North Atlantic–induced wave train mechanisms. The modeling results are then validated against observations from 1900 to 2022 to identify disparities in the CESM1 simulation.

In around 1990, significant shifts occurred in the spatial pattern and temporal evolution of the El Niño‐Southern Oscillation (ENSO), with these shifts showing asymmetry between El Niño and La Niña phases. El Niño transitioned from the Eastern Pacific (EP) to the Central Pacific (CP) type, while La Niña's multi‐year (MY) events increased. These changes correlated with shifts in ENSO dynamics. Before 1990, El Niño was influenced by the Tropical Pacific (TP) ENSO dynamic, shifting to the Subtropical Pacific (SP) ENSO dynamic afterward, altering its spatial pattern. La Niña was influenced by the SP ENSO dynamic both before and after 1990 and has maintained the CP type. The strengthened SP ENSO dynamic since 1990, accompanied by enhanced precipitation efficiency during La Niña, make it easier for La Niña to transition into MY events. In contrast, there is no observed increase in precipitation efficiency during El Niño.

This study explores the key differences between single-year (SY) and multiyear (MY) El Niño properties and examines their relative importance in causing the diverse evolution of El Niño. Using a CESM1 simulation, observation/reanalysis data, and pacemaker coupled model experiments, the study suggests that the Indian Ocean plays a crucial role in distinguishing between the two types of El Niño evolution through subtropical ENSO dynamics. These dynamics can produce MY El Niño events if the climatological northeasterly trade winds are weakened or even reversed over the subtropical Pacific when El Niño peaks. However, El Niño and the positive Indian Ocean dipole (IOD) it typically induces both strengthen the climatological northeasterly trades, preventing the subtropical Pacific dynamics from producing MY events. MY events can occur if the El Niño fails to induce a positive IOD, which is more likely when the El Niño is weak or of the central Pacific type. Additionally, this study finds that such a weak correlation between El Niño and the IOD occurs during decades when the Atlantic multidecadal oscillation (AMO) is in its positive phase. Statistical analyses and pacemaker coupled model experiments confirm that the positive AMO phase increases the likelihood of these conditions, resulting in a higher frequency of MY El Niño events.

Previous studies have emphasized the significance of a strong El Niño preceding La Niña (LN) in the formation of multi-year LN events due to the slow recharge-discharge ocean heat content process. However, observational analyses from 1900 to 2022 reveal that the majority (64%) of multi-year LN events did not necessitate a preceding strong El Niño to generate their second LN, suggesting an overemphasis on traditional views. Instead, here we show that a negative phase of the North Pacific Meridional Mode (PMM) during spring, when the first LN begins to decay, activates the mechanism responsible for triggering another LN and producing a multi-year event. The westward extension of the first LN’s cold anomalies, which interact directly with the eastern edge of the western Pacific warm pool, is highlighted as a crucial factor in the occurrence of a negative PMM. Additionally, the PMM mechanism can create a third LN, leading to triple-dip events.

This study illustrates the considerable improvement in accuracy achievable for long‐lead forecasts (18 months) of the Ocean Niño Index (ONI) through the utilization of a long short‐term memory (LSTM) machine learning algorithm. The research assesses the predictive potential of eight predictors from both tropical and extratropical regions constructed based on sea surface temperature, outgoing longwave radiation, sea surface height and zonal and meridional wind anomalies. In comparison to linear regression model forecasts, the LSTM model outperforms them for both the tropical and extratropical predictor sets. Among all the predictors, the western North Pacific (WNP) index demonstrates the highest prediction skill in ONI forecasts, followed by the North Tropical Atlantic (NTA) index and then the sea surface height index. While other predictors help the LSTM model to forecast either the phase variation of the amplitude variation of the observed ONI, the extratropical WNP predictor enables the LSTM model to forecast both variations. This superiority can be attributed to the involvement of SST anomalies in the WNP region in both tropical and extratropical El Niño–Southern Oscillation (ENSO) dynamics, allowing for the utilization of predictive potential from both components of ENSO dynamics. The study also concludes that the extratropical ENSO dynamics provide a robust source of predictability for long‐lead ENSO forecasts, which can be effectively harnessed using the LSTM model.

This study identifies seasonally-reversed trends in Kuroshio strength and sea surface temperatures (SSTs) within the western North Pacific (WNP) since the 1990s, specifically in the 22° N–28° N region. These trends are characterized by increases during summer and decreases during winter. The seasonally-reversed trends are a result of the asymmetric responses of the WNP to a shift towards the positive phase of the Atlantic multidecadal oscillation (AMO) around the same period. The positive AMO induces an anomalous descent over the North Pacific during summer, leading to the direct strengthening of the gyre. However, during winter, it triggers an anomalous descent over the tropical Pacific, which excites a poleward wavetrain impacting the WNP and causing gyre weakening. The associated responses of the East Asian monsoon and China Coastal Current contribute to the observed seasonally-reversed SST trends. It is noteworthy that the seasonally-reversed trends in gyre strength and SSTs are predominantly observed north of 20° N in the WNP. This limitation arises because the anomalous cyclone within the winter poleward wavetrain is located north of this latitude boundary. Specifically, the clearest trends in gyre strength are observed in the northern segment of the Kuroshio, while the manifestation of SST trends in the Taiwan Strait could potentially be attributed to the influence and enhancement of the East Asian monsoon and the China Coastal Current. Due to the limited length of observational data, statistical significance of some of the signals discussed is rather limited. A CESM1 pacemaker experiments is further conducted to confirm the asymmetric responses of the North Pacific to the AMO between the summer and winter seasons.

During the past two decades, the Maritime Continent (MC) has experienced increased deforestation. Here we show, with ensemble idealized deforestation experiments, that the MC deforestation could potentially alter the complexity (i.e., event‐to‐event differences) of the El Niño‐Southern Oscillation (ENSO) in terms of its spatial pattern and temporal evolution. The deforestation model run increases the occurrences of the Central Pacific and multi‐year types of ENSO compared to the control experiments. This change in ENSO complexity can be attributed to MC's intensification of the subtropical ENSO dynamics, commonly known as the seasonal footprinting mechanism. The deforestation amplifies the mean state of the subtropical high over the northeastern Pacific, leading to an increased dominance of subtropical ENSO dynamics in determining the ENSO pattern and evolution. This idealized coupled climate modeling study suggests that MC deforestation has a potential to alter ENSO's complexity, making El Niño more complex and less predictable.

During 2013–16 and 2018–22, marine heatwaves (MHWs) occurred in the North Pacific, exhibiting similar extensive coverage, lengthy duration, and significant intensity but with different warming centers. The warming center of the 2013–16 event was in the Gulf of Alaska (GOA), while the 2018–22 event had warming centers in both the GOA and the coast of Japan (COJ). Our observational analysis indicates that these two events can be considered as two MHW variants induced by a basinwide MHW conditioning mode in the North Pacific. Both variants were driven thermodynamically by atmospheric wave trains propagating from the tropical Pacific to the North Pacific, within the conditioning mode. The origin and propagating path of these wave trains play a crucial role in determining the specific type of MHW variant. When a stronger wave train originates from the tropical central (western) Pacific, it leads to the GOA (COJ) variant. The cross-basin nature of the wave trains enables the two MHW variants to be accompanied by a tripolar pattern of sea surface temperature anomalies in the North Atlantic but with opposite phases. The association of these two MHW variants with the Atlantic Ocean also manifests in the decadal variations of their occurrence. Both variants tend to occur more frequently during the positive phase of the Atlantic multidecadal oscillation but less so during the negative phase. This study underscores the importance of cross-basin associations between the North Pacific and North Atlantic in shaping the dynamics of North Pacific MHWs.

The occurrence of super typhoons outside the normal typhoon season can result in devastating loss of life and property damage. Our research reveals that the 11-year solar cycle can affect the incidence of these off-season typhoons (from November to April) in the western North Pacific by influencing sea surface temperature (SST) through a footprint mechanism. The solar cycle, once amplified by atmospheric and ocean interactions, generates a noticeable SST footprint in the subtropical North Pacific during winter and spring, which eventually intrudes into the tropical central Pacific and affects the atmospheric conditions, resulting in an increase or decrease in the occurrence of super typhoons during active or inactive solar periods. This mechanism has become more effective since the Atlantic Multi-decadal Oscillation (AMO) shifted to a warm phase in the 1990s, intensifying the subtropical Pacific couplings. An example of this type of off-season super typhoon during an active solar period is Typhoon Haiyan in 2013. By incorporating information about the solar cycle, we can anticipate the likelihood of super typhoon occurrences, thus improving decadal disaster preparation and planning.